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There has been limited research into the predictive value of basic symptoms and their relationship with other psychopathology in patients identified using the 'ultra high risk' (UHR) for psychosis approach. The current study investigated whether basic symptoms, specifically cognitive disturbances (COGDIS), were associated with a greater risk of transition to psychotic disorder and persistent attenuated psychotic symptoms (APS) at medium term follow-up (mean = 3.4 years) in UHR patients, as well as with general psychopathology at baseline. The sample included 304 UHR participants (mean age = 19.12 years) involved in an international multicenter trial of omega-3 fatty acids. UHR individuals who also met the COGDIS criteria (basic symptoms risk criteria) did not have a greater risk of transition than those who met the UHR criteria alone. However, meeting COGDIS risk criteria was associated with a greater likelihood of meeting the UHR attenuated psychotic symptoms risk group (i.e., having persistent attenuated psychotic symptoms) at 12-month follow-up (odds ratio = 1.85; 95% CI = 1.03, 3.32). Greater severity of cognitive basic symptoms was also independently associated with more severe general psychopathology at study entry. The findings do not support the notion that combined risk identification approaches (UHR and basic symptoms) aid in the identification of individuals at greatest risk of psychosis, although this interpretation is limited by the modest transition to psychosis rate (13%) and the time of follow up. However, the findings indicate that basic symptoms may be a clinically useful marker of more severe general psychopathology in UHR groups and risk for persistent attenuated psychotic symptoms., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Considerable research has been conducted seeking risk factors and constructing prediction models for transition to psychosis in individuals at ultra-high risk (UHR). Nearly all such research has only employed baseline predictors, i.e. data collected at the baseline time point, even though longitudinal data on relevant measures such as psychopathology have often been collected at various time points. Dynamic prediction, which is the updating of prediction at a post-baseline assessment using baseline and longitudinal data accumulated up to that assessment, has not been utilized in the UHR context. This study explored the use of dynamic prediction and determined if it could enhance the prediction of frank psychosis onset in UHR individuals. An emerging statistical methodology called joint modelling was used to implement the dynamic prediction. Data from the NEURAPRO study (n = 304 UHR individuals), an intervention study with transition to psychosis study as the primary outcome, were used to investigate dynamic predictors. Compared with the conventional approach of using only baseline predictors, dynamic prediction using joint modelling showed significantly better sensitivity, specificity and likelihood ratios. As dynamic prediction can provide an up-to-date prediction for each individual at each new assessment post entry, it can be a useful tool to help clinicians adjust their prognostic judgements based on the unfolding clinical symptomatology of the patients. This study has shown that a dynamic approach to psychosis prediction using joint modelling has the potential to aid clinicians in making decisions about the provision of timely and personalized treatment to patients concerned., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Impairments in social cognition are believed contribute to disability, particularly for disorders characterized by difficulties in social interaction. There has been little transdiagnostic investigation of this across social cognition domains in young adults. A total of 199 young adults diagnosed with autism spectrum disorder (ASD; N = 53), early psychosis (EP; N = 51), and social anxiety disorder (SAD; N = 64) were compared against neurotypical controls (NT; N = 31) on a battery of lower and higher-order and self-report social cognition measures. For both ASD and EP, participants showed impaired performance on all lower-order emotion recognition tasks and one higher-order social cognition test. Self-reports of empathy were reduced in all clinical groups and particularly in ASD. For SAD, despite showing no objective social cognition impairment, self-reported empathy was reduced to the same level as EP. Discriminant analysis revealed that self-reported empathy and lower-order emotion recognition tests provide best capacity to differentiate groups. Regressions predicting disability revealed depression as the strongest predictor across all disability measures. Empathy provided additional predictive value for social disability and social interaction anxiety. Overall, results support a similar social-cognitive development profile across ASD and EP. While self-reported empathy differentiated between groups, discrepancy between objective social cognition test performance and self-reported empathy in the SAD group suggests probable threat-related self-monitoring report biases that likely further influence all group outcomes. As depression and empathy were the most important predictors of disability, regardless of diagnostic group, research is required to explore targeted interventions for difficulties in these domains to reduce disability.

Individuals are considered Ultra-High-Risk (UHR) for psychosis if they meet a set of standardised criteria including presumed genetic vulnerability (Trait), or a recent history of Attenuated Psychotic Symptoms (APS) or Brief Limited Intermittent Psychotic Symptoms (BLIPS). Recent calls to revise these criteria have arisen from evidence that Trait, APS and BLIPS groups may transition to psychosis at different rates. Concurrently, it has become clear that the UHR status confers clinical risk beyond transition to psychosis. Specifically, most UHR individuals will not develop psychosis, but will experience high rates of non-psychotic disorders, persistent APS and poor long-term functional outcomes. Rather than focus on transition, the present study investigated whether UHR groups differ in their broader clinical risk profile by examining baseline clinical characteristics and long-term outcomes other than transition to psychosis. Four UHR groups were defined: Trait-only, APS-only, Trait+APS, and any BLIPS. Participants (N=702) were recruited upon entry to early intervention services and followed-up over a period of up to 13years (mean=4.53, SD=3.84). The groups evidenced similar symptom severity (SANS for negative symptoms, BPRS for positive and depression/anxiety symptoms) and psychosocial functioning (SOFAS, GAF, QLS) at baseline and follow-up as well as similar prevalence of non-psychotic disorders at follow-up. Our findings demonstrate that UHR groups evidence a similar clinical risk profile when we expand this beyond transition to psychosis, and consequently support maintaining the existing UHR criteria., (Copyright © 2017. Published by Elsevier B.V.)

Background: Optimizing functional recovery in young individuals with severe mental illness constitutes a major healthcare priority. The current study sought to quantify the cognitive and clinical factors underpinning academic and vocational engagement in a transdiagnostic and prospective youth mental health cohort. The primary outcome measure was 'not in education, employment or training' ('NEET') status., Method: A clinical sample of psychiatric out-patients aged 15-25 years (n = 163) was assessed at two time points, on average, 24 months apart. Functional status, and clinical and neuropsychological data were collected. Bayesian structural equation modelling was used to confirm the factor structure of predictors and cross-lagged effects at follow-up., Results: Individually, NEET status, cognitive dysfunction and negative symptoms at baseline were predictive of NEET status at follow-up (p < 0.05). Baseline cognitive functioning was the only predictor of follow-up NEET status in the multivariate Bayesian model, while controlling for baseline NEET status. For every 1 s.d. deficit in cognition, the probability of being disengaged at follow-up increased by 40% (95% credible interval 19-58%). Baseline NEET status predicted poorer negative symptoms at follow-up (β = 0.24, 95% credible interval 0.04-0.43)., Conclusions: Disengagement with education, employment or training (i.e. being NEET) was reported in about one in four members of this cohort. The initial level of cognitive functioning was the strongest determinant of future NEET status, whereas being academically or vocationally engaged had an impact on future negative symptomatology. If replicated, these findings support the need to develop early interventions that target cognitive phenotypes transdiagnostically.

Background: People with schizophrenia have high rates of substance use which contributes to co-morbidity and premature mortality. Some evidence suggests people at-risk for psychosis have high rates of substance use. We aimed to assess substance use in a help-seeking cohort, comparing those at-risk and not at-risk for psychosis, and to establish any relationship with clinical symptoms., Method: Participants were help-seeking youth presenting to mental health services in Sydney and Melbourne. 279 (34.8%) were at-risk for psychosis, and 452 (56.4%) did not meet criteria for a psychotic disorder or risk for psychosis. The excluded individuals were made up of 59 (7.4%) young people who met criteria for a psychotic disorder and 11 (1.4%) who were unable to be evaluated. We assessed the association of substance use involvement with risk status and clinical symptoms using multivariate regression., Results: Individuals at-risk for psychosis had significantly higher tobacco, alcohol and cannabis use than those not at-risk. Multivariate analysis revealed at-risk status was significantly associated with higher alcohol involvement scores when adjusting for age and gender, but no association was found for cannabis or tobacco. At-risk status was no longer associated with alcohol involvement when cannabis or tobacco use was added into the analysis., Conclusion: Tobacco smoking, alcohol consumption and cannabis use are common in help-seeking youth, particularly those at-risk for psychosis. It is important to consider co-occurring use of different substances in adolescents. Early substance misuse in this phase of illness could be targeted to improve physical and mental health in young people., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Cognitive remediation (CR) is an effective treatment for several psychiatric disorders. To date, there have been no published studies examining solely first-episode psychiatric cohorts, despite the merits demonstrated by early intervention CR studies. The current study aimed to assess the effectiveness of CR in patients with a first-episode of either major depression or psychosis. Method Fifty-five patients (mean age = 22.8 years, s.d. = 4.3) were randomly assigned to either CR (n = 28) or treatment as usual (TAU; n = 27). CR involved once-weekly 2-h sessions for a total of 10 weeks. Patients were comprehensively assessed before and after treatment. Thirty-six patients completed the study, and analyses were conducted using an intent-to-treat (ITT) approach with all available data., Results: In comparison to TAU, CR was associated with improved immediate learning and memory controlling for diagnosis and baseline differences. Similarly, CR patients demonstrated greater improvements than TAU patients in psychosocial functioning irrespective of diagnosis. Delayed learning and memory improvements mediated the effect of treatment on psychosocial functioning at a marginal level., Conclusions: CR improves memory and psychosocial outcome in first-episode psychiatric out-patients for both depression and psychosis. Memory potentially mediated the functional gains observed. Future studies need to build on the current findings in larger samples using blinded allocation and should incorporate longitudinal follow-up and assessment of potential moderators (e.g. social cognition, self-efficacy) to examine sustainability and the precise mechanisms of CR effects respectively.

Microstructural white matter changes have been reported in the brains of patients across a range of psychiatric disorders. Evidence now demonstrates significant overlap in these regions in patients with affective and psychotic disorders, thus raising the possibility that these conditions share common neurobiological processes. If affective and psychotic disorders share these disruptions, it is unclear whether they occur early in the course or develop gradually with persistence or recurrence of illness. Utilisation of a clinical staging model, as an adjunct to traditional diagnostic practice, is a viable mechanism for measuring illness progression. It is particularly relevant in young people presenting early in their illness course. It also provides a suitable framework for determining the timing of emergent brain alterations, including disruptions of white matter tracts. Using diffusion tensor imaging, we investigated the integrity of white matter tracts in 74 patients with sub-syndromal psychiatric symptoms as well as in 69 patients diagnosed with established psychosis or affective disorder and contrasted these findings with those of 39 healthy controls. A significant disruption in white matter integrity was found in the left anterior corona radiata and in particular the anterior thalamic radiation for both the patients groups when separately contrasted with healthy controls. Our results suggest that patients with sub-syndromal symptoms exhibit discernable early white matter changes when compared with healthy control subjects and more significant disruptions are associated with clinical evidence of illness progression.

Currently, there are no validated neurobiological methods for distinguishing different pathophysiological pathways in young patients presenting in the early phases of major psychiatric disorders. Hence, treatments are delivered simply on the basis of their possible effects on nonspecific symptom constructs such as depression, cognitive change or psychotic symptoms. In this study, the ratios (relative to creatine) of key metabolites (N-acetyl aspartate, myoinositol, glutamate and glutathione) were measured with proton magnetic resonance spectroscopy ((1)H-MRS) within the anterior cingulate cortex of 88 young persons presenting with major mood or psychotic symptoms. We derived empirically (using a cluster analytical technique) three subgroups of subjects on the basis of their patterns of in vivo brain biochemistry. The three subgroups were distinguished (from each other) by all the four metabolites, in particular, glutathione and glutamate. By contrast, the groups could not be distinguished by differences in terms of other demographic, functional or clinical measures. We propose that this (1)H-MRS-based subclassification system could be used as the basis for much more specific tests of novel intervention strategies (notably, antioxidant and glutamatergic therapies) early in the course of major psychiatric disorders.